Senior Compiler Engineer

Description

About the AI Division:

The AI Division is a unique and dedicated group within Ceva, driving innovation in Machine Learning and Generative AI architectures for edge devices and cloud inference.

Our R&D domains span Neural Network Processors (NPU), Vision DSPs, and advanced AI algorithms for applications across smartphones, tablets, automotive, surveillance cameras and many more edge AI systems.

We combine cutting-edge hardware IP design with embedded software and system-level solutions, enabling the next generation of intelligent and energy-efficient devices.

About the Role:

As a senior compiler engineer, you will own the design and development of Ceva’s open source based toolchain and graph compiler. You will drive technical solutions end-to-end, deliver compiler capabilities across all Ceva hardware targets, and help mentor engineers. Our team embraces an AI-agentic development flow, leveraging AI coding agents to accelerate engineering productivity, and we are looking for engineers who champion this approach.

Responsibilities:

Design and develop Ceva’s open source based toolchain targeting custom DSP and NPU architectures.

Drive design and delivery of graph compilation flows: transformations, operator mapping, and code generation.

Champion AI-agentic development practices — integrating AI coding agents into day-to-day engineering workflows.

Own complex components end-to-end, from architecture and design through implementation and delivery.

Provide technical guidance and mentorship to engineers; conduct code reviews.

Collaborate with hardware architecture, algorithms, and software teams globally.

Analyze and optimize toolchain output for performance and correctness across Ceva processor families.

Requirements

• B.Sc. in Computer Science, Electrical Engineering, or related field.
• 5+ years of hands-on experience in software development.
• Strong C++ skills; Python proficiency is a plus.
• Proven ability to own and deliver complex software components independently.
• Solid software engineering fundamentals.
• Strong communication skills; comfortable in a global, multi-site environment.

Advantages

• Hands-on experience with AI-agentic development — using AI coding agents (e.g. GitHub Copilot, Cursor, Claude Code) to drive and accelerate software development.
• Hands-on experience with LLVM/Clang — backend, instruction selection, register allocation, or code generation.
• Familiarity with MLIR — dialects, passes, or graph-level compiler development.
• Knowledge of AI/ML frameworks and neural network execution.
• Experience with embedded systems, DSP or NPU architectures.
• M.Sc. or higher in a relevant field.